Abstract

Massive Online Open Courses (MOOCs) have
been growing in popularity with educational researchers, instructors, and
learners in online environments. Online discussions are as important in MOOCs
as in other online courses. Online discussions that occur in MOOCs are influenced
by additional factors resulting from their volatile and voluntary participation
structure. This article aims to examine discussions that took place in MobiMOOC
in the spring of 2011, a MOOC structured around mobile learning. This line of
inquiry focused on language from the discussions that contained emotive
vocabulary in the MobiMOOC discussion forums. Emotive vocabulary is words or
phrases that are implicitly emotional (happy, sad, frustrated) or relate to
emotional contexts (I wasn’t able to…). This emotive vocabulary, when present,
was examined to determine whether it could serve as a mechanism for predicting
future and continued participation in the MOOC. In this research, narrative
inquiry approach was used in order to shine a light on the possible predictive
qualities of emotive text in both participants who withdrew from the course as
well as moderately or moderately active participants. The results indicated
that emotive vocabulary usage did not significantly predict or impact
participation retention in MobiMOOC.

Introduction

In recent years, the educational
community has been experimenting with form (Open courses), content (Open Educational
Resources), and accessibility (Open Access). This experimentation can serve to
mitigate the negative impact of reduced funding; further, it signals a
professed desire to hinge educational pedagogy to the realities of emerging
modernity. In short, it is a belief held by many that the present educational
structure will not efficiently serve the needs of tomorrow. The authors believe
that combining technologies that embrace the complexity of knowledge production
with pedagogical formats that allow learners to build knowledge by means of
filtering that complexity, will allow a new educational balance to emerge (de
Waard et al., 2011b). This paper focuses on one such manner of experimentation
designed to maximize the affordance of an open, often free of cost,
collaborative learning culture that is available online: the Massive Online
Open Course (MOOC).

A MOOC ascribes to the principles of
universal access: it is widely available to most everyone with internet access
and free to join. Enrolment sizes tend to be high, generally over 500
participants. Pedagogically it embraces an open, social structure, and a
constructivist, connectivist manner of knowledge production. In short, anyone
is free to join, create, interact, analyze, and reflect according to his or her
own learning needs. There is pedagogical structure, but little authoritative
control aside from that imposed by the network of participants itself. Learners
join, participate, and withdraw at high frequency. This paper focuses on the
high levels of participation and low levels of retention often experienced in
the MOOC format through the specific context of the discussion forums of
MobiMOOC, a course designed around the theme of mobile learning.

Researchers have examined message
patterns to determine how earlier messages in a discussion chain affect future
participation. For example Chen & Chiu (2008), examined the content and
elements of group dynamics and Bajali & Chakrabarti (2010), examined how
the perceived richness of discussions affects participation. The role of gender
has been researched as a factor in participation and the type of language used
(Guiller & Durndell, 2007; Lin & Overbaugh, 2009; Yates, 2001).
Frequency analysis of how and when people log in (Hung & Zhang, 2008),
software usability and sociability (Lu, Phang, Yu, 2011) and even
procrastination have been examined in online interactions (Michinov, Brunot, Le
Bohec, Juhel, Delaval, 2011). Much of this research forms the basis of this
paper’s focus into the analysis of MobiMOOC discussions.

MobiMOOC Design

MobiMOOC ran for six weeks between April
2 and May 14, 2011. It was organised by Inge de Waard who also remained present
as an active participant throughout the course. Leading researchers and
practitioners in the mLearning field facilitated MobiMOOC and the course
featured 1827 messages on topic (de Waard et al., 2011b). There were 536
participants in MobiMOOC, substantial because the course was only advertised
informally through blogs and Twitter. The topics covered in the six weeks of
MobiMOOC included mLearning planning, mLearning for development (M4D), leading
edge innovations in mLearning, interaction between mLearning and a mobile
connected society and mLearning in K-12 environments. Each topic was
facilitated by an expert in the particular subject area. All the facilitators
in MobiMOOC (Inge de Waard, Judy Brown, Niall Winters, David Metcalf, John
Traxler, and Andy Black) were guides on the side, each putting forward as many
learning actions and follow-ups as they wanted, as each of these facilitators
were also voluntarily engaged in the course.

The course was free for anyone interested
in the topic of mLearning and after its completion the content remained
available as an open repository for mLearning resources. Although most
resources offered by the facilitators and participants were openly accessible
online, some of the academic resources (citations offered by MOOC participants)
were behind database paywalls.

All participants (including the
facilitators) were able to receive new information and construct new knowledge
that fit their own personal learning needs. As such, participants were in
charge of their own learning. The participants were able to get information
that was relevant to them by asking the entire group for insights. The course
organiser suggested three categories for learner participation, indicating the
importance of self-regulated learning to the participants. These three types
were as follows:

Lurking participants: follow the course, look at the recordings, and browse the
available course resources. The benefit to the lurking participant was to get
some idea of what is going on in the field of mLearning.

Moderately active participants took one or two topics and engaged in the conversation with
everyone involved. The benefit for the moderately active participants was that
they developed more in-depth knowledge in that area of mLearning and were able
to exchange notes and expertise, getting answers to questions they may have
had.

Memorably active participants participated in at least five of the six topics. They developed an
mLearning proposal in their area and received peer and expert help. Although a
template was provided, it was clearly communicated that the writing of the
proposal would be done by each of the participants. Memorably active
participants received a certificate of participation (de Waard et al., 2011a).

The discussion on MobiMOOC took place in
many forms. The organiser of MobiMOOC created an official course wiki and an
official Google Group through which discussion could take place. Due to the
open nature of the MOOC, in addition to the official MobiMOOC venues,
participants also blogged about MobiMOOC topics (and shared those links in the
Google Group). Additionally, there was a Facebook group created for MobiMOOC
and many participants tweeted with the hashtag #MobiMOOC. The flexibility in
participation format and the large number of participants contributed to a
large amount of textual and non-textual information generated by MobiMOOC
participants.

Participants of MobiMOOC

By looking at the forum posts, we
determined that by the end of the MOOC, 13.3 % of the overall participants
of the MOOC completed the course as active participants (74 people).
Approximately 5.8 % of the participants were memorably active (32 people).
The majority (86.7 %) were either lurkers or dropped the course. At the
end of the course, a survey was distributed amongst the participants. In this
survey, the majority (82.5 %) of the active participants indicated that
they used what they learned in MobiMOOC in their day-to-day work, and they took
the opportunity (65 %) to work on an mLearning project while participating
in MobiMOOC.

MobiMOOC participants were also quite
diverse in their backgrounds. The survey shows that participants were diverse
in both age (21-30=15 %, 31-40=22.5 %, 41-50=25 %, 51-60=27.5 %,
61-70=10 %) as well as gender (male=57.5 %, female=42.5 %). This
may indicate that the MOOC format attracts people from across what is perceived
to be the traditional technology dichotomies. The diversity of MobiMOOC was
also evident in the careers of participants. An analysis of the discussion
forum posts, where participants self-identified their professional areas as
part of their introduction to the course, indicated that a substantial amount
of participants came from the ranks of Instructional Designers (32 %).
This included Instructional Systems Specialists, Instructional Media
Specialists, Instructional Technology Specialists, and Instructional Designers;
and Educators (26 %), which included Teachers, Instructors and Professors.
Managers of Instructional Technology (9 %) and Students (9 %) also
made up other large segments of MobiMOOC participants. The remainder of the
participants were quite diverse including librarians, doctors, administrators,
researchers in varying fields, and developers.

Participants in the MobiMOOC course
comprise a diverse set of students, teachers, researchers, and educational
technology enthusiasts at a wide range of institutions ranging from elementary
school teachers to university faculty to researchers at government facilities.
Geographically, there was a large concentration of participation in Europe and
North America with little participation in South America, Africa, Asia and Oceania, as indicated in our MobiMOOC crowdmap (Figure 1).

Figure 1. MobiMOOC Crowdmap

Most of the participants worked in Higher
Education (49 %). This might be expected since information about MOOCs
tends to circulate by word of mouth in academic circles. MOOCs also tend to be
designed by educators for educators. In our survey, K-12 educators and
professional were the second largest group (18 %), while instructional
designers and learning professionals from private firms (13 %) came in
third. Other groups included government employees in various learning roles (7 %),
non-profit employees (9 %) and self-employed learning professionals (4 %).
MobiMOOC also included one participant who was a retired educator.

Purpose of the study

Using the discussion boards as evidence
of the construction of a personal narrative of engagement with the course,
MobiMOOC discussion logs were analysed. Our research team aimed to determine
the following:

if the vocabulary that MobiMOOC participants
used when communicating about the MOOC, and through the MOOC to fellow
participants, gave clues as to how these participants felt about the MOOC;

how participants felt about the progress that
they made during the MOOC, and their self-assessment of their continued participation;

if levels of participation, and overall learner
retention in MOOCs can be predicted through textual analysis of the emotive
language used by MOOC participants;

if certain keywords or key-phrases signal
increased participation and/or retention, while other keywords predict an
increase in dropout rate or demotion of participants from their current status
(active or memorably active).

Significance of the study

The significance of determining such
keywords or key-phrases is immensely important to course facilitators; should
certain keywords or key-phrases be found that signal increased or decreased
participation in a course, automated responses to those signals can be
developed to foster renewed participation. For example, automated alerts that alert
facilitators of a potential increase of dropouts or lurkers could be built into
the MOOC management systems, be these systems traditional Learning Management
Systems (LMS) or social media groups. Facilitators could then adjust the course
to promote greater participation within it or address learners in danger of
dropping out to assess the reasons behind their demotivation and possibly get
them engaged into the course again.

Even though there were many sources of
textual data from MobiMOOC, including Twitter posts or delicious bookmarks
shared with the #mobimooc tag, a Facebook group, blog posts, an official Google
Group and an official wiki, the text analysed for this project was the text
collected from the MobiMOOC Google group. This was the MOOC’s centre of
activity for participant communication.

Methodology

Type of research

Using a narrative inquiry approach with
an analysis of language frequency (emotive language), discussion participation
frequency, and participant interactions, the authors began this inquiry with
the belief that there are predictive qualities in the language used both by the
participants who withdrew from the course as well as those who became
moderately or memorably active. To address these questions requires an analysis
of the discussion logs as evidence of a personal narrative of engagement, or
disengagement, from the course. The qualitative data collected from the
discussions of the participants were then subjected to an analysis to gauge the
general level of engagement with the MobiMOOC.

Data collection and ethical considerations

Data collected for this research was taken
from the text-based discussions for the MobiMOOC Google Group discussion forum,
which served as the main hub of activity for MobiMOOC. In addition, if MobiMOOC
participants publicized their blog posts as they pertained to MobiMOOC, those
blog posts as well as comments to them were also analysed. The discussion data
that we analyzed are publicly available data whose original use was not for research
purposes. Great care was taken to insure the anonymity of the participants and,
as such, names, website addresses, and other identifying information were
removed to reflect this consideration.

Although no explicit privacy statement
was posted in either the MobiMOOC wiki or the MobiMOOC Google Group
establishing specific expectations of privacy or openness, it is our belief
that the public availability of these discussion venues under investigation,
Google Groups and publicly available blog posts, being open to the public,
mitigates the need for informed consent. It is our belief that these actions
ascribe to the principles of the Ethics Guide of the Association of Internet
Researchers (2002) in that the material to be used is primarily for an analysis
of retention and participation in open courses and, as such, risk is minimal.

Structure of the data analysis

For the purpose of this research, we
determined that an analysis of the Google Group discussion logs for MobiMOOC
would yield the greatest results for determining the nature of retention and
withdrawal of participants on the course. The reason for picking Google Group
discussion data over other MOOC sources is that the Google Group was the
central, and official, discussion forum, and as such, it can be viewed as a common
denominator for all MobiMOOC participants. MOOCs tend to have high (>50 %)
withdraw/dropout rates and MobiMOOC was no exception; of the more than 500
participants that began the course, a little over 70 were active in some sort
of discussion by the final week; possible lurking participants were not taken
into account as these participants are not trackable. This high withdrawal rate
poses challenges to adoption of the MOOC as a widespread learning format for a
diverse range of disciplines and learners. Retention strategies can possibly
mitigate this high withdrawal rate.

This research does not presuppose a
particular level of participation in the MobiMOOC course, but rather attempts
to gauge that engagement with the course based on an analysis of the discussion
board transcripts. The premise of our investigation is that an increase in
engagement or in disengagement with the course was signalled in the form of
emotive language in the early weeks of the course (Weeks 1-3), signalling a
change in participation patterns in the second half of the course (Weeks 4-6). Two
members of the research team reviewed the discussion board transcripts and
seemingly ‘meaningful’ exchanges were coded according to the following three
categories:

Possible professional mismatch between course
objectives and participant expectations

Trepidation, uncertainty, unfamiliarity, some
indication of a lack of confidence in ability

Professional expertise, experience, confidence,
self-assuredness

The coding reflects the assumption that
not everyone will participate or withdraw from the course based solely on
uncertainty, unfamiliarity with the course structure, or a perceived lack of
confidence in navigating the learning in the course. Rather, increased
engagement or disengagement from the course might signal satisfaction or
dissatisfaction in meeting professional learning needs (coded as equating to a
professional mismatch between the course and the professional needs of the
participant); conversely, professional expertise, experience, and
self-confidence might signal an increased engagement with the course and other
course participants. What is not accounted for in this analysis are those
students classified as lurkers (lurking as following rather than actively
engaging the course); there is very little data available to track their
participation with the MobiMOOC course and as of yet very little work has been
performed on lurkers in MOOCs (Kop, 2011).

After the six weeks of discussion board
transcripts were coded, further narrative analysis was conducted to determine
whether participants were signalling either their withdrawal or their increased
participation in the course.

Connecting to relevant research frameworks

This form of analysis has precedent with
online transcripts being used by researchers to investigate the process of
social construction of knowledge (Gunawardena, Carabajal & Lower, 2001) and
critical thinking (Bullen & O'Brien, 1997; Webb, Newman & Cochrane, 1994). Our
research attempts to replicate this form of analysis not directly towards
evidence of social construction of knowledge or critical thinking, but rather
towards the notion of social engagement with the course, a facet affected by a
variety of factors including learner self-confidence and self-empowerment,
professional expectations and learning satisfaction, and social acceptance.

By analysing the online transcripts for
evidence of language as well as parsing out relevant passages for further
analysis, our goal is “to reveal information that is not situated at the
surface of the transcripts,” but rather address participant patterns of
engagement with the course that might signal satisfaction (De Wever et al.,
2006). Our research focuses on transcript analysis, a “research methodology
that builds on procedures to make valid inferences from text” (Rourke,
Anderson, Garrison & Archer, 1999). Further, inspiration was drawn from the
analytical framework of learner engagement as put forth by Henri (1992), which
recognises that a participant dimension of learner engagement can be analysed
through an analysis of overall participation, which is measured through the
total number of messages, responses, and accesses to the discussion, and the
active participation in the learning process, which is the number of statements
directly made to learning. In the MOOC format, the network and participation
often become the learning itself so it is our belief that Henri’s facets of
participation blend heavily into one another (1992). As such, this research
focuses on overall participation and emotional signals within that
participation.

Also of interest to this research is the
presence of social messages in the discussion transcripts, such as jokes,
compliments, and greetings (Rourke et al., 1999). These are generally
considered meaningful and motivating exchanges between students and important
in establishing social presence in online discussion formats. Social presence
might generally be categorized as affective responses, interactive responses,
and cohesive responses (De Wever et al., 2010). There is evidence of all three
of these types of social presence responses on the MobiMOOC discussion boards.

In the following sections, we describe
how we analysed and withdrew valid inferences from the text of the transcripts.

Findings & results

First pass

Our initial examination of the data
entailed re-reading and re-familiarizing ourselves with the content and the
dynamics of the course. This process allowed us to develop a more detailed
picture of the week-by-week discussions in MobiMOOC from the perspective of the
ethnographer, rather than as a participant. At the time of the course, the
authors were not participating as researchers; rather, we participated as
fellow MobiMOOC participants. Our personal recollections were quite positive
regarding our participation in the MOOC and about our fellow participants. In
this review of the transcripts, we aimed to determine if our own recollections
were more favourable than the prevailing sentiment in the MOOC.

Reading through
six weeks of MobiMOOC transcripts revealed that our recollections of the
MobiMOOC environment were accurate. During the course, as well as before and
after the course[1], there
was excitement exhibited around the topic of mobile learning (mLearning),
around the MobiMOOC course itself, and towards our collegiality. Many
individuals took the opportunity to share their own experiences and knowledge
on the topic, provided feedback to fellow participants who were undertaking
mLearning projects, and provided academic resources for further reading and study.
No explicit contradictions were revealed during our initial examination of the
discussion data exploring the accuracy of our initial impressions of the MOOC. It
was at this time that we also went through and coded these discussions for
indications of expertise, trepidation and uncertainty, and potential mismatch
between expectations of the participant and what the MOOC had to offer.

Referring to our LIWC analysis (Figure A.2.1), positive emotive vocabulary use substantially outnumbers the use
of negative vocabulary in the weekly discussions. Even in Week 4, when there is
a dip in the quantity of positive vocabulary use, there is a corresponding dip
in negative vocabulary use, which indicates that there were fewer discussion
posts during Week 4 than other weeks of MobiMOOC. We did see an increase in
negative vocabulary between Week 1 and Week 2, and during this period we did
see a small dip in positive vocabulary between Week 1 and Week 2. However as a
whole the positive outweighed the negative.

The word frequency clouds were very
revealing (Figures A.1.1 - A.1.6). All weeks show that participants were
sticking to the topic of mobile learning and not going “off topic.” In Weeks 5
and 6, the MOOC seemed to become a little more intimate, given that
participant’s first names surfaced with much greater frequency[2]. Throughout the six weeks of the course,
even though thematic vocabulary (mLearning related) was the majority of the
vocabulary present, considerable positive emotive vocabulary was also present.
However, we did not see this same pattern for negative emotive vocabulary.
During Week 1 we also saw considerable social vocabulary, such as greetings and
introductions, which is to be expected during the first week of a course when
participants introduce themselves.

Third pass

Our first two passes over the discussion
data did not indicate whether positive and negative emotive vocabulary can
predict an increase or decrease in participation. We examined the discussion
analytics to see how many posts were posted each week, how many participants
participated each week, and what categories these participants belonged to.

For this pass, we weren’t analysing the discussion
data itself; rather, we analysed the discussion and participant counts. We
examined a pre-MOOC and a post-MOOC period in addition to the six weeks of
MobiMOOC itself. These pre- and post-MOOC periods contain data for one month
before the beginning date of MobiMOOC and one month after the completion of the
last day of MobiMOOC. What we observed is that there is an increase in
discussion posts between Week 1 and Week 2 (Figure A.3.2), perhaps
attributable to a “honeymoon period” where participants are getting acclimated
to the MOOC. However, participation starts to decline after Week 2 and
maintains a plateau in the final two weeks of the MOOC and the post-MOOC
period.

From a participant point of view (Figure A.3.1), MobiMOOC hit a peak of active participants in Week 1. However,
after Week 1 the number of participants started declining, again reaching a
plateau in the final weeks of MobiMOOC (Weeks 5, 6, and the Post-MOOC period). Interesting
to note is that the post-per-participant ratio actually increases over the
duration of the MOOC (Figure A.3.4). It is higher than both the pre-MOOC
period and that of the first week of the MOOC, again reaching a plateau for
Weeks 5 and 6 and the Post-MOOC period.

Taking this into account, and examining
the participant heat map (Wilkinson & Friendly, 2009) (Figure
A.4.1), we note that during Weeks 1 and 2, the majority of posts were contributed
by individuals who participated in one or two weeks of the MOOC, while in
subsequent weeks more of the discussion was done by people that had been in the
MOOC for a longer period. To borrow Kim’s terminology (2000, in Bishop, 2009),
more of the MOOC discussions were made by participants who emerged as Elders,
Leaders and Regulars in the latter half of the MOOC, while in the
beginning of the MOOC more of the discussion was made by participants who were Novices or Lurkers. What is interesting is that almost one third (⅓)
of the registered participants (Figure A.4.3) of the MOOC fall into this
category of Lurker[3] or Novice. We know that many Lurkers and Novices did not convert to
Regulars or Leaders, however, the emotive vocabulary use in the discussion
forums does not tell us why this is as Lurkers and Novices are notably present
in the first two weeks of the course.

Final pass

Our final analysis layer was that of a
narrative analysis of select passages from the discussion transcripts. Our team
chose passages from each of the categories that we coded; we examined the
content, specifically from the first Week of MobiMOOC. This week saw the most
active participants and was the second most active week on MobiMOOC.

Note that in the following passages have
been made anonymous, including the omission of all organizational names,
locations, and website locations.

Trepidation, uncertainty, unfamiliarity, some indication
of a lack of confidence in ability

The following passage is an example from
ourcategory indicating potential trepidation, uncertainty,
unfamiliarity, and some indication of a lack of confidence in ability:

Hello All,

I'm ________, instructional technologist
at _________. I work in our Center for Teaching & Learning. We offer
workshops, consultations & more to help faculty use technology in
pedagogically sound ways in their courses.

Our university does not yet have a
strategy for mobile learning so I'm hoping to develop a proposal to present
to my director and ultimately our Provost.

I'm little more than a newcomer to
mLearning but I see it's value. We use Moodle as our learning management
system (or VLE) but we really haven't looked much at making it more
"mobile." Personally, I have an iPad and use it as more than an
eReader (although I do love reading books on it).

Still trying to get a feel for this MOOC
& Google group - a bit overwhelmed with all the topics so far.

___________

I am new to google groups. Where do I
make my profile?

_______, I think this is the most recent
scoop on Google Groups and linking to your Google Profile - from Google
Groups support: http://goo.gl/MSM9V

Hi Folks,

I'm finding the sheer volume of stuff
being generated in the MOOC quite overwhelming (and the course hasn't even
started yet)! =8-0

Suspecting I'm not alone, I'm wondering
if those who have already participated in things like CCK11 and LAK11 could
offer us newbies to MOOCs some tips on how to cope?

Perhaps these could be added to the wiki?

Cheers,

__________

I know this will go against the flow, but
taking on a new role this year as a year 8 co-ordinator, it's a huge problem.
Can someone please read this blog post I made and offer some advice.

Also read the comments that have been
made.

(URL)

Thanks,

____________

I read your blog post and I perfectly
agree with you. At least i may country we haven't arrived to that point but
if we give them mobile phones from a very early age we will be encouraging
them to do what they are doing in your country.

Educating students and teachers in mobile
etiquette is good but will they use it as they were taught or will they use
it as they wish and want?

_____________

Hi __________,

I'm not sure this counts as advice or
help, but it sounds more like a problem with certain students and their
parents rather than mobile devices per se I've heard of similar issues where
parents have turned up at schools demanding audience with teachers or heads
over similar issues they consider unfair. These people exist with or without
the phone, its a social issue rather than a technological issue. In the same
way as taking inappropriate pictures is, but that hasn't stopped you using
the iPods.

It's interesting to consider the flip
side to this too. How frustrating is it to be the victim of an abusive or
incompetent teacher, when the authorities don't believe you. Have a look at
thishttp://www.handheldlearning2009.com/proceedings/video/905-video/303-z... (the whole video is worth watching, but the relevant bit is 4:40 to 6:40) I
blogged about that talk and the whole conference here(URL) - I think it has
relevance to what's happening with the MOOC movement too.

____________

I've posted on the site too, but I agree
with ________. This is not about the device, it is about behaviour. One of
the things I noted was that the teacher is the adult in the room. The teacehr
can expect certain standards, including students putting phones on airplane
mode, and putting them in full view on the desk. Anotehr point I raised was that
people tend to get a bit hysterical about phones as if they are inherently
bad. If students brought to school an objectionable magazine or photograph,
would the school ban all magazines and photographs? Stepping back and seeing
the situation for what it is. In the cases described in the blog, it seems to
me kids are playing teacher against parent. A united and clear front is what
is required, as well as rules of engagement. it is about behaviour not an
object.

Some relevant posts about mobile phone
use in US schools has started up over in the Kicking Off thread (URL)

(relevant posts will be time stamped just
before this one)

________________

I signed up for this free MOOC (Massive
Open Online Course) about mobile learning a few days ago, having seen a link
during an #eltchat about the subject on Twitter on Wednesday evening. During
the said chat, I felt like I was missing something - like I wasn't really
part of the gang. I was ashamed of my own ignorance, so I decided to do
something about it and registered for the course.

What on earth is a MOOC? This was my
first question, so I turned to the oracle that is YouTube & found several
videos including this one which gave me the answer:

Having established what a MOOC was, I now
had to get to grips with what mlearning was. I lurked around the mobiMOOC
wiki and the group discussion pages. I read all the information provided by
the facilitators and the posts from course participants. And then came the
revelation! I'm not as ignorant as I thought I was! Unfamiliar with the
jargon certainly, but not totally clueless in reality.

You see, I already engage in mlearning
every day. I just didn't know I was doing it! I use my mobile phone to talk,
to send & receive messages, and to take photos which I sometimes use in
class. I use my i-Pod Touch to access the internet via wi-fi, to manage my
contacts and my diary, to keep notes, and to listen to podcasts and share
them with my students. I use my laptop to do everything else, including to
write my blog. All of these things, I now understand, are mlearning!

Forgive me for being a bit late to the
party, but I'm here now and I won't be lurking behind the curtains any more!
I'm starting to go through the course materials and following up on links
provided by my fellow participants. I'm hugely encouraged by what I have seen
so far and I'm really looking forward to being more actively involved over
the next few weeks.

__________, ciao!

Thanks for sharing your first thoughts.
Looking at what you are doing, I am sure you will come up with an interesting
mLearning project.

Nice. You are right, I think. We do a lot
of the "learning" without thinking about how things have changed or
giving a name to it.

I am "mobile learning" right
now as I read your post on my phone and communicate with you on this blog.

Hi __________, learning has a broad
meaning I see. Almost anything is learning. I like your books in the
background picture of the blog.

Do you not allow pingback in your blog?
That would make comments easier.

regards ____________

Thanks for the comments - much
appreciated!

_________, - you will have to enlighten
me - I did say I wasn't au fait with much of the jargon!! So, what is
'pingback' and how do I get it? See, I'm learning all the time!!

Pingback is a little trick your weblog
will do for you.

I do not know why your blog does not do
the trick, maybe it is not activated?

On Pingback is an explanation on
Wikipedia.

In Blogger in the dashboard you could
choose preferences / backlinks and choose not hide. In that place you will
see a information link on backlinks.

Thanks for this!!

In the exchanges, we see something all
too common in online education and with MOOCs in particular: students are
attempting to negotiate the technology that is a prerequisite for participating
in online courses. They are attempting to filter, or create processes to deal
with any sort of potential information overload that comes with being part of
an online course, especially a massive online course like MobiMOOC. We believe
that there was some trepidation on the part of these participants. However the
expressed statements that these participants are not alone might mean that
there is a possibility for participants to help out fellow participants both
with the technology (as seen with one participant helping another with their
Google Profile), and with the MOOC content itself.

Professional expertise, experience, confidence,
self-assuredness.

The following are two examples passages
from our coding indicating professional expertise, experience, confidence,
self-assuredness.

In the following exchanges, we see that
participants are showing their professional expertise by indicating where they
work, what they are involved in, providing advice to fellow MobiMOOC
participants, and sharing with others links to their social media profiles so
that, presumably, other participants may follow them. This professed
professional expertise projects a narrative of confidence.

Hi fellow mobiMOOC participants!

I'm based in ________, Scotland in the medical school at the University of ________ where I work in the eLearning
Team. My particular interest is in how mlearning can best be used to support
medical education and specifically in the undergraduate curriculum.

I have a blog, but have decided to set up
a Posterous site to post my reflections on mobiMOOC together with any web
clippings I find interesting relating to mlearning. I've just posted my
thoughts on the first learning activity 'Mobile learning and me' and you can
read it here (URL).

Looking forward to the next few weeks!

____________

Hi, I am ________, working at _______in Madrid, Spain. In the elearning field for 4 years. Some affirmations that can describe
parts of myself:

- A journalist and a marketing girl
before elearning showed up in my life

- Interested in mlearning cause I am
currently leading a related project for the financial sector.

- Using my company own platform, known as
________, to develop it.

- Recently speeched about the subject at
_______ 2011.

- Addicted to any kind of new technology
that can make a change, meaning devices, social network and so.

I am expecting to be part of mobimooc
with a very high level of participation, and be remembered "As an
memorably active participant." let's see if I get my goal.

This is my first mooc course, first time
I hear about the concept, and I already love it!

Looking forward to join the adventure.

Hi ________,

Here in ______ we have an extremely high
mobile penetration rate with over 100%. I worked on a project with fisherfolk
and it started with the desire of one of the training institutes to deliver
content to fisherfolk via podcast on a mobile phone.

The back ground research led to a survey
to find out first if they used a mobile phone, what kind of phone and how
they used the phone (talk, sms, check lottery numbers). We also asked if they
used there phones for work and how, and if they would be willing to pay for service
that helped their work. For these surveys it was done face to face
(verbal/written) in the local communities. This method was chosen so
technology and literacy did pose a barrier to gathering the information.

It is crucial to understand your target
audiences level of use, the technology available, the environment it will be
used in and also to understand their needs and wants because whatever you
develop must be relevant or meet a need or else they will not use it. Once
this information was gathered a possible project could then have been developed.
The involvement of the community or target group through the project process
from development to implementation is crucial to its success.

My best advice to you is to spend time
with the group you are working with, observe how they use their phones in
their work, ask questions so you fully understand how they use their phones.
Find out what language they use to talk about their phones. Get their
thoughts on your project ideas, if you find someone in the community who is interested
in your ideas use them as a sounding board for ideas, survey questions, how
to deliver the survey etc...

These are my thoughts and experiences on
how to assess a target audience.

____________

Possible professional mismatch between course objectives
and participant expectations

Finally, these two example passages from
our category indicating possible professional mismatch between course
objectives and participant expectations are revealing.

In the following set of introductions, we
observe some potential mismatch between the participants, what they wrote about
themselves and the topics of MobiMOOC, which were posted on the MobiMOOC Wiki.
It is possible these participants connected with others who shared the same
goals, but perhaps MobiMOOC may not have been the venue for them. These
participants do in fact fall into the 1-2 Week participation group.

Hi all,

my name is __________ and I manage the
Learning Laboratories at the Centre for Learning Sciences and Technologies at
the _________. I am looking at m-learning topics since some years with a
focus on context-aware systems, mobile field trip support, and situated
learning and information access.

Main topics in the field of m-learning we
are currently exploring are:

- Ubiquitous access to information: so
how can we support users to access information not only on the PC, the mobile
device but synchronized with cloud storage support.

- Learning experiences in context: how
can we use sensors and context information to enhance learning experiences
and information filtering and mobile learning services in context, to get
more efficient, and effective learning.

- Orchestration of learning experiences,
how can we arrange and create physical spaces linking real world and digital
information to support learning in overarching scripts.

Me and a group of colleagues maintain a
mobile learning blog at: (URL) Current topics I am personally interested in
are also eBook content and iPad in the classroom and we have some pilot
projects with schools in Heerlen and using mobiles with adults in city
excursion.

Hi all,

This is my first MOOC, so I'm still
feeling my way around! I work as a content publishing manager at ________ (my
team creates technical documentation). I'm interested in how mobile devices should
fit into that space. I posted the tools I most often use on my mobile and
some links to interesting videos I found on my blog, here: (URL)

Cheers,

_____________

Hi,

Ways I am connecting with the MOBImooc at
this point are:

This email group and the course WIKI

Twitter: ___________following list for
#mobimooc

Blog: (URL)

Looking forward to good conversations and
info!

I'm a senior analyst at the research firm
_____________. I cover the L&D space including mobile learning. I'm
preparing for a session at this year's mLearnCon on the readiness of
organization's technology infrastructure for mLearning.

Caveats for this study

While conducting this study our team was
surprised not to find any significant indicators of participation in the
emotive vocabulary of participants. In hindsight, perhaps this was to be
expected due to the open nature of a MOOC. Some see MOOCs as being a venue with
an open-door policy as participants can come and go as they please. The low
barrier to entry and departure of MOOCs may signal to participants a lack of
requirement to justify their departure from the MOOC; since participants do not
have to stay for the full duration of the course, any perceived or factual
negativity (expressed through the use of negative emotive vocabulary) may not
be recorded because participants simply leave without indicating, one way or
another, why they left.

An important consideration for this study
is the distinction between lurkers and dropouts. In MobiMOOC, 48 % of the
participants did not post on Google Groups while the MOOC was in-session. These
individuals may be lurkers and active in their own ways (reading and following
along) that are not visible to other participants and researchers or they may
have dropped out. Additionally, we see that about 9 % of registered users
participated in the pre- and post-MOOC periods, but not during the MOOC.
Emotive vocabulary use did not seem to indicate why these registered users did
not participate during the MOOC.

Finally, about 24 % of registered
participants participated in one or two weeks of the course[4], but again emotive language use alone does
not describe why these participants participated in ⅓ or less of the
course and not in the remaining ⅔ of the MOOC. We know that these
participants wrote something during those weeks, but we do not know if they dropped
out or lurked. Some examples of 1-2 week participant patterns are participation
in Week 1 and Week 6; Participation in Week 1 and 2; and Participation in Week
2 and 6. As researchers we do not know if they were following along in the
weeks they were not active, or if they decided to “jump out” in those
weeks and “dip in” in the weeks that they participated. We also do not
know if they were dissatisfied and decided to drop out without exhibiting any
of the emotive language that we were searching for.

Further Research

As mentioned at the beginning of the
paper, the official Google Group was but one of the locations that participants
in MobiMOOC could use to discuss items relating to their participation in
MobiMOOC. The Google Group did act as a central hub for all MobiMOOC
discussions, but there were other venues available to participants as well.
Other venues included a participant created Facebook group, Twitter discussions
and posts using the #mobimooc hashtag, and the official MobiMOOC wiki where participants
could contribute to the creation of an open resource around the topic of
mLearning.

It would be interesting to compare our
results from this Google Group discussion analysis with an analysis of Facebook
group messages and Twitter posts with the #mobimooc hashtag in order to compare
both participation patterns, type of content shared and discussed, and emotive
vocabulary use. In addition to emotive vocabulary, social vocabulary use might
be interesting to examine in MobiMOOC discussions, based on Henri’s framework
(1992). This framework consisted of participative, social, interactive and
metacognitive dimensions that look at active participation as part of the
learning process, and how the active participation and learning might influence
lurkers to join in the discussion and learning.

Another model to consider is the Rourke,
Anderson, Garrison, & Archer (1999) social presence model which examines
social interaction between participants. Looking at overt social interaction
between participants, and social cues might be a better indicator of future
participation. Perhaps in order to get more engagement from lurkers, future
MOOCs may employ a more traditional starter-wrapper-moderator discussion
architecture (Hara, Bonk, Angeli, 1998) which in turn might get MOOC lurkers
participants to engage a bit more and perhaps aid in separating the lurkers
from the dropouts or no-shows.

Following an internal MobiMOOC research
team discussion, it became clear that the ethical considerations of analysing
participant’s online data from social media and other sources is not yet well
defined. The new, open and public nature of learning, and the long-term
visibility of submitted and shared content, bring analysis of this data into an
ethical grey area for research. Further investigation into this matter is also
needed.

Conclusion

We started this research project with the
aim of analysing the discussion forum logs of MobiMOOC, a Massive Online Open
Course that lasted six weeks in the spring of 2011. Our goal was to determine
if the emotive language that participants used in the discussion forums served
as predictors of participation in future discussion topics in the MOOC. Our
research did not indicate any correlation between the use of emotive language
and increases or decreases of participation in the course. One reason might be
that, unlike face-to-face environments where linguistic and paralinguistic
behaviour might signal such changes in participation, in an online environment
paralanguage is not visible. It may also be that these participants are
dropping out of the course without saying anything. MOOC participants have
mentioned ideas for how MOOC designs might better track lurkers and non-lurkers
and offered ideas for MOOC designers to better gauge the level of increased or
decreased participation at a more granular level (Koutropoulos, 2011).

As the MOOC progressed in Weeks 5 and 6,
the discussions seemed to become more intimate given that participant’s first
names surfaced with much greater frequency. Also interesting is that the
post-per-participant ratio increases over the duration of the MOOC (Figure A.3.4), after an initial dip (Week 3) when perhaps the novelty of the MOOC
had worn off. Presumably in this period, participants who had decided to
participate in the MOOC remained, and those who decided to not participate or
lurk dropped off. Lastly, it is interesting to note that the discussion in the
first half of the MOOC was mostly dominated by individuals who participated in
only the first two weeks of the MOOC, while in the second half of the MOOC
(post dip) the forum was dominated by individuals who had participated in more
than three weeks of the course.

MOOCs suggest possibilities for research
in many areas, including research in the areas of learner motivation,
engagement, social presence and instructor presence. There are, however, areas
in which MOOCs need to evolve in order to better facilitate the capturing and
analysing of data relevant to their structure. Some of these categories of data
include: determining who is merely ‘window shopping’ in the initial periods of
a MOOC, who is a lurker, who is an active participant, and when and why
participants drop out (completely). Some Learning Management Systems (LMS) do
have existing capacity for such learner and learning analytics. MOOCs have been
carried out using a variety of tools and so may or may not use an established
LMS. Therefore, access to that rich data is not always available. In order to
better understand the learners and MOOC participation, such data may need to be
available for analysis and systems that facilitate this collection may need to
be built.

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A.2. LIWC Analysis Charts

A.3. Weekly Post &
Participant Counts

A.4. Participants

[1] Discussion data examined was collected
from a period of one month before the MOOC’s official start and one month after
the end of the sixth, and final, week.

[2] This may be a reason to examine other
methodologies and frameworks in future studies such as those discussed by
Rourke et al. (1999) and Henri (1992)

[3] For this discussion, a Lurker is someone who participated in the
Pre-MOOC period, but did not participate in discussions during the MOOC. There
many have been more lurkers, but these are the only quantifiable lurkers.

[4] Some of these participants also
participated in either the pre-MOOC or post-MOOC period, so some members of
this classification can be seen as having participated 2-3 weeks in total.